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Quick Win for Negotiating with Supplier Using Simulation Results


Quick Win for Negotiating with Supplier Using Simulation Results

Equipment part breakdown in the Intel factories, as in many factories is inevitable. These failures typically cause capacity constraints and ultimatley cost the corporation time and money. Equipment parts can be repaired locally or may require shipping to the vendor for repair. Since the repair loop takes significant time, it is necessary to have extra spare parts on-hand to keep the equipment running while broken parts are repaired. It is pertinent to avoid overbuying of the spare parts, as they are very expensive. Intel needed a model of the repair loop to increase the visibility of problems such as broken parts accumulating at the vendor repair center and sites over purchasing spare parts. At the AnyLogic Conference 2014, Victor Chang, Software Engineer at Intel presents an AnyLogic simulation that was developed to model the complexities and variability

Provider Payment Reform to Reduce Rates of Cesarean Delivery


Provider Payment Reform to Reduce Rates of Cesarean Delivery

“Cesarean delivery” is a method of childbirth in which a surgeon cuts through the pregnant woman’s abdomen and uterus to deliver the baby. The more natural method of childbirth is called “vaginal delivery”, in which the baby leaves the mother’s uterus through her vaginal canal. Ideally, cesarean delivery would only be used when vaginal delivery would endanger the life or health of the child or mother, because cesarean delivery involves major abdominal surgery that is accompanied by much greater risks for both mother and child than vaginal delivery. Cesarean delivery also costs about 50 percent more. Over the last 40 years, the U.S. rate of cesarean delivery has increased dramatically.

Modeling Healthcare at Different Abstraction Levels


Modeling Healthcare at Different Abstraction Levels

There are many cases of simulation modeling in healthcare. Application areas can vary, from process optimization in hospitals to macrolevel agent-based epidemiology models. Due to its multimethod nature, AnyLogic allows models to be built at various abstraction levels. A good illustration of how researchers and consultants can apply the same tool to different problems is the three models built by the Stockholm County Health Administration in Sweden. The models included macro, meso, and micro abstraction level applications in healthcare simulation. The microlevel model simulated the maternity ward in a hospital that was currently under construction. The purpose of the model was to support discussions related to which resources, capacity, and work methods were required in the new ward. One relevant discussion was whether to keep mother and child in the same room during their entire stay or to have dedicated rooms for antenatal care, delivery, and postnatal care.

Simulating Rail Network Operation Challenges with and without the Rail Library


Simulating Rail Network Operation Challenges with and without the Rail Library

While the extensive rail library was a key reason that CSX chose AnyLogic as its general purpose simulation tool for the Network Modeling, Operations Research, and Process Excellence groups, the other libraries and methods have added significant value as well. In fact, the first major project where AnyLogic was used did not utilize the rail library. After reviewing the problem in more detail, a discrete-event simulation model was built to help managers studying train throughput. The model simulated the demand of empty trains from five coal mines, as well as the fulfillment of the demand. A supply-chain-like network model was created, which implemented logic to depict the demand, supply and staging of empty trains. The trains were modeled as moving entities across the network. By varying values of relevant parameters, users can infer the impacts of different factors to the train throughput (i.e. siding staging capacity and loading speeds at the coal mines). The model provides a way for decision makers to gain insight into the system to help identify the maximum possible throughput. The objective was to identify the best operational/capital strategy to handle the increased business.

Analysis of Management Strategies for Aircraft Production Ramp-up


Analysis of Management Strategies for Aircraft Production Ramp-up

Growing competition and a high demand for individual and highly sophisticated products in combination with shorter innovation cycles is leading to a rising number of ramp-ups especially in Small batch production. Daily challenges such as late changes and missing maturity of high Technology products and processes create significant risks. Since 2012 a group of 14 European companies and research institutes have developed novel planning and control solutions in the European public funded project ARUM (Adaptive Production Management; www.arum-project.eu) to overcome those challenges in production ramp-up. The validation of the developed control strategies and their implementation into novel planning and scheduling solutions within a realistic industrial environment is mandatory and several industrial use Cases have been selected, e.g. an Airbus system installation flowline in Hamburg.

Production Plan Optimization at Ice Cream Manufacturing Plant


Production Plan Optimization at Ice Cream Manufacturing Plant

Conaprole, the biggest dairy production company in Uruguay, produces more than 150 SKUs in their ice cream plant, using five production lines, and up to five different packaging configurations for each line. The company plans ice cream production on a 12-month rolling basis as part of the Sales & Operations Planning process, and the demand plan varies a lot due to seasonality. The factory management needs to prepare the production lines for the peak season during the low season, taking into account product shelf life and the warehouse’s freezing cameras’ capacity and costs. The factory was often unable to meet the high season demand that generated stock-outs. In addition, management found it very difficult to reschedule quickly their detailed plans due to the challenges they faced including bottlenecks, production process constraints, and staff turnover.

Managing River Logistics with Simulation


Managing River Logistics with Simulation

Inland waterway logistics have their own special aspects that include high seasonality due to weather conditions, long delivery times, restricted door-to-door delivery capabilities, and more. On the other hand, river transport is cheap, environmentally friendly, and allows large amounts of goods to be carried. Barges are widely used to carry both bulk cargo and containers. Simulation can help companies justify switching to river logistics by comparing water transportation to other means in terms of costs, throughput, or shipping time. Shipping operators can use simulation to optimize routing and fleet management policies, taking into account uncertainties, breakdowns, bottlenecks, weather conditions, and water level. The following is a success story of river transport simulation-based optimization in South America.

Customer-Centric Transportation Network Modeling


Customer-Centric Transportation Network Modeling

The sphere of public transportation services in Australia is undergoing a transformation in response to a number of drivers, such as a need for inter-modal integration and widespread introduction of consumer information technologies. However, in order to better address new challenges associated with these changes one must first develop an understanding of the dynamic relationships between the way public transportation system operates and the many ways in which people use it to achieve desired mobility. The public transportation company employed PwC to develop a solution for better decision-making and problem-solving. A model was built using AnyLogic 7 as a platform to unify and animate various static data into a dynamic system of interactions. The model is based on three sources of information: network structure provided in GIS format, service timetable in tabular form and ticket sales information gathered from a variety of systems.

Predictive Analysis in a Risk-Free Environment


Predictive Analysis in a Risk-Free Environment

From warehousing decisions and transportation planning, to minimizing expenses and maximizing service level, optimizing a supply chain and logistics network is a complex and multi-faceted exercise. In addition to the day-to-day challenges, prepare your organization for the unexpected; a port shutdown, trade policy changes or natural disasters. These and other unexpected events can have a devastating impact on your organization. Mitigating the impact of external factors by ensuring alternative mission-critical capability will help prepare your business to overcome such adversity. Compared to traditional methods, utilizing simulation modeling for crisis management, business continuity, cyber attacks, disaster recovery, reorganization and other “what-if” scenarios is a low-cost, relatively quick, easy-to-run solution. Simulation modeling allows you to visualize these key factors and engage decision makers to ensure your plan is as effective as possible, and that you are prepared for whatever you encounter.

Case Study: Major US Airline decides NOT to Charge Additional Fees


Case Study: Major US Airline decides NOT to Charge Additional Fees

A major U.S. airline was facing a situation where opportunities to extend the existing strategy were limited, coupled with an increasing cost structure due to competition, commodity prices, and acquisition integration activities. The airline began to explore several options to generate new profits through ancillary products or changes to existing policies and was under intense pressure from board members, Wall Street and various analysts to do so. PwC, the world’s second largest professional services network, was employed by the Airline to model the predicted impact of the client’s ticket market share and company brand sentiment after introducing new products or policy changes.